Outlier detection in logistic regression and its application in medical data analysis

Citation

Ahmad, Sanizah and Mohamed Ramli, Norazan and Midi, Habshah (2012) Outlier detection in logistic regression and its application in medical data analysis. In: 2012 IEEE Colloquium on Humanities, Science & Engineering Research (CHUSER 2012), 3-4 Dec. 2012, Kota Kinabalu, Sabah. (pp. 503-507).

Abstract

The application of logistic regression is widely used in medical research. The detection of outliers has become an essential part of logistic regression. It is often observed outliers have a considerable influence on the analysis results, which may lead the study to the wrong conclusions. Many procedures for the identification of outliers in logistic regression are available in the literature. In this paper, four methods for outlier detection have been investigated and compared through numerical examples.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Science
DOI Number:	https://doi.org/10.1109/CHUSER.2012.6504365
Publisher:	IEEE
Keywords:	Logistic regression; Outlier; Residual; Detection
Depositing User:	Nabilah Mustapa
Date Deposited:	04 Aug 2020 02:41
Last Modified:	04 Aug 2020 02:41
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/CHUSER.2012.6504365
URI:	http://psasir.upm.edu.my/id/eprint/45052
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